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SECTION 4 - CROSS-CUTTING

ChatGPT Prompts for Financial Modeling & Analysis

All roles — IB modeling, IM valuation, S&T scenario work

A model is only as good as the assumptions no one interrogated. These prompts put a skeptic in the room: they walk your three-statement drivers for internal consistency, pull apart a DCF's assumptions and build the sensitivity map, and reconcile why two 'comparable' names trade at different multiples. The model structures and stress-tests; it does not invent inputs. Paste your figures, make it flag anything it had to assume, and check the math yourself.

3 free prompts you can run right now

Financial Analysis & ModelingFREE

Three-statement driver interrogation + model sanity-check

You have a working model (or a target's historicals) and want a fast, structured challenge of the assumptions before it goes to a VP or PM.

You are a skeptical senior analyst reviewing a three-statement model. I will paste the key financials and my forecast assumptions. Do the following, in this order:

1) Restate, in a TABLE, the operating drivers you infer from the historicals (revenue growth, gross margin, EBIT margin, capex % of sales, NWC as % of sales, cash conversion). Flag any that look internally inconsistent.
2) Interrogate my forward assumptions line by line. For each, tell me whether it is aggressive, conservative, or in-line versus the historical trend and typical sector ranges, and WHY. Ask me the 5 questions a VP would ask before signing off.
3) Build the implied bridge from this year's EBITDA to the terminal-year EBITDA and tell me what share of the growth is volume, price, margin, or acquisition.
4) List the 3 assumptions the valuation is MOST sensitive to and the ones that are cosmetic.
5) Give me a one-paragraph 'what would have to be true' summary I could defend in a model review.

Do not invent numbers. If something is missing, ask for it. Here are the financials and assumptions:
[PASTE HISTORICALS + YOUR ASSUMPTIONS]

Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it. Mark every claim I should verify externally before relying on it. Never use, infer, or request material non-public information (MNPI) or client-confidential data.
Financial Analysis & ModelingFREE

DCF assumption interrogation + sensitivity map

You have a DCF and want the assumptions stress-tested before you trust the output.

You are a skeptical senior analyst reviewing a DCF for [COMPANY]. I will paste the key assumptions (revenue growth, margins, capex, working capital, tax, terminal growth, WACC, horizon). Do this:
1. Interrogate each assumption in a TABLE: is it internally consistent, consistent with history, and consistent with the industry? Flag any that look aggressive or conservative and why.
2. Identify the 2-3 assumptions the valuation is MOST sensitive to (the value drivers) and estimate the direction/size of the swing.
3. Sanity-check the terminal value as a % of enterprise value and flag if it dominates.
4. Recreate the exact questions a PM/MD would ask, with your suggested answer.
Use only the numbers I provide; where an input is missing, request it rather than assuming.

Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it. Mark every claim I should verify externally before relying on it. Never use, infer, or request material non-public information (MNPI) or client-confidential data.
Financial Analysis & ModelingFREE

Multiples reconciliation: why the gap

Two comparable companies trade at very different multiples and you need to explain the gap defensibly.

You are a valuation analyst reconciling a multiple gap. [COMPANY A] trades at [multiple] and [COMPANY B] at [multiple]. I will give their financials. Produce:
1. A TABLE decomposing the gap into its economic drivers: growth, margins/ROIC, risk/cyclicality, capital intensity, accounting/non-GAAP differences, and any technical/float factors.
2. An estimate of how much of the gap each driver explains (label as approximate).
3. Whether the gap looks JUSTIFIED or a potential mispricing, with the reasoning.
4. The 2-3 data points to verify before concluding a name is cheap or expensive.
Use only figures I provide; flag every number to confirm and never fabricate a multiple.

Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it. Mark every claim I should verify externally before relying on it. Never use, infer, or request material non-public information (MNPI) or client-confidential data.

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7 more Financial Analysis & Modeling prompts in Pro

The full Financial Analysis & Modeling set — plus every other desk's prompts, personalized to your role — is part of Pro. Here's what's inside:

Financial Analysis & Modeling

Unit-economics & cohort model review

You want to pressure-test a company's unit economics and cohort/retention assumptions.

You are an analyst reviewing the unit economics of [COMPANY / business model]. I will give the drivers (CAC, LTV, gross margin, churn/retention, payba
Financial Analysis & Modeling

Working-capital & cash-conversion diagnostic

You want to know whether reported earnings are actually converting to cash.

You are a forensic-minded analyst assessing earnings quality for [COMPANY]. I will paste the relevant financials. Produce:
1. A cash-conversion read:
Financial Analysis & Modeling

Financial-ratio trend diagnostic

You want a fast, structured read of a company's financial health and where it's trending.

You are an analyst running a ratio diagnostic on [COMPANY] across the periods I provide. Produce:
1. A TABLE of key ratios by category — profitability
Financial Analysis & Modeling

Revenue bridge + variance decomposition

You need to explain a revenue (or margin) change by decomposing it into its real drivers.

You are an FP&A / equity analyst building a revenue bridge for [COMPANY], period [A] to [B]. I will give the data. Produce:
1. A BRIDGE decomposing th
Financial Analysis & Modeling

Scenario & sensitivity table design

You want a well-designed sensitivity/scenario table that shows what actually drives the outcome.

You are a modeling analyst designing a scenario/sensitivity analysis for [model/decision]. I will give the model's key drivers and base-case outputs.
Financial Analysis & Modeling

ROIC vs WACC value-creation check

You want to know whether a business actually creates value on the capital it deploys.

You are an analyst assessing value creation for [COMPANY]. I will provide the inputs (NOPAT or operating income and tax, invested capital, cost of cap
Financial Analysis & Modeling

Capex & reinvestment-runway analysis

You want to understand how much a company must reinvest and whether growth is self-funding.

You are an analyst assessing the reinvestment economics of [COMPANY]. I will provide the data (capex, D&A, revenue, operating cash flow, growth). Prod
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Reality guardrail: These prompts make the model reason from data you paste — they do not source or verify figures for you. Check every number against the primary document, keep MNPI and client-confidential data off consumer AI tools, and follow your firm's AI-use policy. Educational only, not financial advice.

Frequently asked

Can ChatGPT build a financial model?

It can scaffold the logic, write the formulas, and interrogate your assumptions — but you provide the data and own the output. The reliable pattern is to paste your drivers and have the model check them for internal consistency, surface the two or three assumptions that swing the answer most, and design the sensitivity table. Treat every number it returns as unverified until you've checked it. Educational only, not advice.

How do you use AI for DCF analysis?

Not to produce a valuation you trust blindly, but to pressure-test the one you built. Paste your DCF assumptions — growth, margins, WACC, terminal value — and ask the model which inputs the output is most sensitive to, where your assumptions look aggressive versus history, and what a bear case would change. The intrinsic value is still your judgment; the model just makes the fragile assumptions visible.

Will AI make Excel and financial modeling obsolete?

No. AI speeds up the tedious parts — writing formulas, catching inconsistencies, drafting commentary — but the structure, the assumptions, and the accountability stay with the analyst. The people who benefit most treat it as a fast, tireless reviewer of their own work, not a replacement for understanding the model.

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This content was generated with AI assistance and reviewed by a human editor. For informational and educational purposes only — not financial advice and not a recommendation to buy or sell any security. Not a registered investment adviser. Past performance does not guarantee future results. All investing involves risk. Do your own research (DYOR) and verify every AI output against the original source before it informs a decision. Do not paste material non-public information (MNPI), client PII, or confidential deal data into consumer AI tools; follow your firm's data-handling and AI-use policy. © 2026 ECWE Ventures LLC · AI Finance Brief.